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Do NFL teams make rational decisions? What factors potentially affect the probability of wining a game in NFL? How can a team come back from a demoralizing interception? In this study we begin by examining the hypothesis of rational…

Applications · Statistics 2017-02-08 Konstantinos Pelechrinis , Evangelos Papalexakis

In fantasy sports, strategic thinking-not mere luck-often defines who wins and who falls short. As fantasy cricket grows in popularity across India, understanding whether success stems from skill or chance has become both an analytical and…

Applications · Statistics 2025-12-23 Supratim Das , Sarthak Sarkar , Subhamoy Maitra , Tridib Mukherjee

Deep neural networks (DNN) have achieved remarkable success in various fields, including computer vision and natural language processing. However, training an effective DNN model still poses challenges. This paper aims to propose a method…

Machine Learning · Computer Science 2024-07-03 Hejie Ying , Mengmeng Song , Yaohong Tang , Shungen Xiao , Zimin Xiao

Here several perfect simulation algorithms are brought under a single framework, and shown to derive from the same probabilistic result, called here the Fundamental Theorem of Perfect Simulation (FTPS). An exact simulation algorithm has…

Probability · Mathematics 2017-04-13 Mark Huber

The paper studies the highly prototypical Fictitious Play (FP) algorithm, as well as a broad class of learning processes based on best-response dynamics, that we refer to as FP-type algorithms. A well-known shortcoming of FP is that, while…

Optimization and Control · Mathematics 2015-04-21 Brian Swenson , Soummya Kar , Joao Xavier

In all competitions where results are based upon an individual's performance the question of whether the outcome is a consequence of skill or luck arises. We explore this question through an analysis of a large dataset of approximately one…

Physics and Society · Physics 2021-06-09 Joseph D. O'Brien , James P. Gleeson , David J. P. O'Sullivan

This paper considers mean field games with optimal stopping time (OSMFGs) where agents make optimal exit decisions, the coupled obstacle and Fokker-Planck equations in such models pose challenges versus classic MFGs. This paper proposes a…

Numerical Analysis · Mathematics 2023-10-10 Chengfeng Shen , Yifan Luo , Zhennan Zhou

Fantasy basketball has a rich underlying mathematical structure which makes optimal drafting strategy unclear. A central issue for category leagues is how to aggregate a player's statistics from all categories into a single number…

Methodology · Statistics 2024-09-10 Zach Rosenof

This paper presents a novel approach for optimizing betting strategies in sports gambling by integrating Von Neumann-Morgenstern Expected Utility Theory, deep learning techniques, and advanced formulations of the Kelly Criterion. By…

Portfolio Management · Quantitative Finance 2023-07-27 Vélez Jiménez , Román Alberto , Lecuanda Ontiveros , José Manuel , Edgar Possani

NBA team managers and owners try to acquire high-performing players. An important consideration in these decisions is how well the new players will perform in combination with their teammates. Our objective is to identify elite five-person…

Applications · Statistics 2023-09-28 Susan E. Martonosi , Martin Gonzalez , Nicolas Oshiro

For regression tasks one often leverages large datasets for training predictive machine learning models. However, using large datasets may not be feasible due to computational limitations or high data labelling costs. Therefore, suitably…

Machine Learning · Computer Science 2024-08-15 Paolo Climaco , Jochen Garcke

In this paper, we present a novel approach for optimising long-term tactical and strategic decision-making in football (soccer) by encapsulating events in a league environment across a given time frame. We model the teams' objectives for a…

Artificial Intelligence · Computer Science 2021-02-19 Ryan Beal , Georgios Chalkiadakis , Timothy J. Norman , Sarvapali D. Ramchurn

Performative prediction is an emerging paradigm in machine learning that addresses scenarios where the model's prediction may induce a shift in the distribution of the data it aims to predict. Current works in this field often rely on…

Machine Learning · Computer Science 2025-09-03 Guangzheng Zhong , Yang Liu , Jiming Liu

Previous work on fantasy basketball has established methods for optimizing team construction for head-to-head formats. This has been facilitated by the straightforwardness of calculating the objective function for those formats, given that…

Methodology · Statistics 2025-01-03 Zach Rosenof

Understanding team formations and player positioning is crucial for tactical analysis in football (soccer). This paper presents a flexible method for formation recognition and player position assignment in football using predefined static…

Machine Learning · Computer Science 2025-07-01 Joris Bekkers

In the NFL draft, teams must strategically balance immediate player impact against long-term value, presenting a complex optimization challenge for draft capital management. This paper introduces a framework for evaluating the fairness and…

Applications · Statistics 2025-04-11 Tanmay Grandhisiri

American college football faces a conflict created by the desire to stage national championship games between the best teams of a season when there is no conventional playoff system to decide which those teams are. Instead, ranking of teams…

Physics and Society · Physics 2007-05-23 Juyong Park , M. E. J. Newman

Even skilled fantasy football managers can be disappointed by their mid-season rosters as some players inevitably fall short of draft day expectations. Team managers can quickly discover that their team has a low score ceiling even if they…

Predicting outcomes in sports is important for teams, leagues, bettors, media, and fans. Given the growing amount of player tracking data, sports analytics models are increasingly utilizing spatially-derived features built upon player…

Machine Learning · Computer Science 2022-07-29 Peter Xenopoulos , Claudio Silva

With the growing prevalence of smart grid technology, short-term load forecasting (STLF) becomes particularly important in power system operations. There is a large collection of methods developed for STLF, but selecting a suitable method…

Machine Learning · Computer Science 2018-11-06 Cong Feng , Jie Zhang